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      "SGD : 0.26439956024927935\n",
      "Momentum : 0.07892038160437441\n",
      "AdaGrad : 0.14015519921107386\n",
      "Adam : 0.005838720399712239\n",
      "==========iteration9100=============\n",
      "SGD : 0.4401701426204936\n",
      "Momentum : 0.07820461724935263\n",
      "AdaGrad : 0.19412548481861086\n",
      "Adam : 0.03403939774986258\n",
      "==========iteration9200=============\n",
      "SGD : 0.262839974584937\n",
      "Momentum : 0.03977124206932611\n",
      "AdaGrad : 0.09876076192543513\n",
      "Adam : 0.004677744015592962\n",
      "==========iteration9300=============\n",
      "SGD : 0.1644074105536735\n",
      "Momentum : 0.01586190698557638\n",
      "AdaGrad : 0.05514215323833036\n",
      "Adam : 0.007035673558096792\n",
      "==========iteration9400=============\n",
      "SGD : 0.2214885421249432\n",
      "Momentum : 0.04063279038763299\n",
      "AdaGrad : 0.09772992056588077\n",
      "Adam : 0.002071923066002022\n",
      "==========iteration9500=============\n",
      "SGD : 0.25661537087626995\n",
      "Momentum : 0.0658638372104945\n",
      "AdaGrad : 0.14439466160091288\n",
      "Adam : 0.018895945744902158\n",
      "==========iteration9600=============\n",
      "SGD : 0.33512319314559547\n",
      "Momentum : 0.05668305871821294\n",
      "AdaGrad : 0.15936747580155647\n",
      "Adam : 0.03487120301467258\n",
      "==========iteration9700=============\n",
      "SGD : 0.2772322028370537\n",
      "Momentum : 0.04447331459343785\n",
      "AdaGrad : 0.13440544660975745\n",
      "Adam : 0.037743136899377264\n",
      "==========iteration9800=============\n",
      "SGD : 0.2554616237605719\n",
      "Momentum : 0.07713230066498386\n",
      "AdaGrad : 0.1430827748152578\n",
      "Adam : 0.012989603462894983\n",
      "==========iteration9900=============\n",
      "SGD : 0.3791682479978124\n",
      "Momentum : 0.0746937529918074\n",
      "AdaGrad : 0.19964137403336393\n",
      "Adam : 0.04418166138561749\n"
     ]
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "from dataset.mnist import load_mnist\n",
    "from common.two_layer_net import TwoLayerNet\n",
    "from common.optimizer import *\n",
    "from common.util import smooth_curve\n",
    "\n",
    "# 0.读入MNIST数据\n",
    "(x_train, t_train), (x_test, t_test) = load_mnist(normalize=True)\n",
    "\n",
    "# 超参数\n",
    "iters_num = 10000       # 训练轮数\n",
    "train_size = x_train.shape[0]   # 训练数据量\n",
    "batch_size = 100        # 单批次数量\n",
    "learning_rate = 0.1     # 学习率\n",
    "\n",
    "# 1.进行实验设置\n",
    "optimizers = {}\n",
    "optimizers['SGD'] = SGD()\n",
    "optimizers['Momentum'] = Momentum()\n",
    "optimizers['AdaGrad'] = AdaGrad()\n",
    "optimizers['Adam'] = Adam()\n",
    "\n",
    "networks = {}\n",
    "train_loss = {}\n",
    "for key in optimizers.keys():\n",
    "    networks[key] = TwoLayerNet(input_size=784, hidden_size=50, output_size=10)\n",
    "    train_loss[key] = []\n",
    "\n",
    "# 2.开始训练\n",
    "for i in range(iters_num):\n",
    "     # 获取小批量数据\n",
    "    batch_mask = np.random.choice(train_size, batch_size)\n",
    "    x_batch = x_train[batch_mask]\n",
    "    t_batch = t_train[batch_mask]\n",
    "\n",
    "    for key in optimizers.keys():\n",
    "        # 计算梯度\n",
    "        grads = networks[key].gradient(x_batch, t_batch)\n",
    "        optimizers[key].update(networks[key].params, grads)\n",
    "\n",
    "        loss = networks[key].loss(x_batch, t_batch)\n",
    "        train_loss[key].append(loss)\n",
    "\n",
    "    if i % 100 == 0:\n",
    "        print(\"==========iteration\" + str(i) + \"=============\")\n",
    "        for key in optimizers.keys():\n",
    "            loss = networks[key].loss(x_batch, t_batch)\n",
    "            print(key, \":\", str(loss))\n",
    "\n",
    "# 3.绘制图形\n",
    "markers = {\"SGD\": \"o\", \"Momentum\": \"x\", \"AdaGrad\": \"s\", \"Adam\": \"D\"}\n",
    "x = np.arange(iters_num)\n",
    "for key in optimizers.keys():\n",
    "    plt.plot(x, smooth_curve(train_loss[key]), marker=markers[key], markevery=100, label=key)\n",
    "\n",
    "plt.xlabel(\"iterations\")\n",
    "plt.ylabel(\"loss\")\n",
    "#plt.ylim(0, 1)\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  }
 ],
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  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.6"
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 },
 "nbformat": 4,
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}